Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture (FESB), University of Split, R. Boskovica 32, 21000 Split, Croatia.
Polytechnic of Sibenik, Trg Andrije Hebranga 11, 22000 Sibenik, Croatia.
Sensors (Basel). 2021 Dec 30;22(1):255. doi: 10.3390/s22010255.
As the rapid growth of mobile users and Internet-of-Everything devices will continue in the upcoming decade, more and more network capacity will be needed to accommodate such a constant increase in data volumes (DVs). To satisfy such a vast DV increase, the implementation of the fifth-generation (5G) and future sixth-generation (6G) mobile networks will be based on heterogeneous networks (HetNets) composed of macro base stations (BSs) dedicated to ensuring basic signal coverage and capacity, and small BSs dedicated to satisfying capacity for increased DVs at locations of traffic hotspots. An approach that can accommodate constantly increasing DVs is based on adding additional capacity in the network through the deployment of new BSs as DV increases. Such an approach represents an implementation challenge to mobile network operators (MNOs), which is reflected in the increased power consumption of the radio access part of the mobile network and degradation of network energy efficiency (EE). In this study, the impact of the expected increase of DVs through the 2020s on the EE of the 5G radio access network (RAN) was analyzed by using standardized data and coverage EE metrics. An analysis was performed for five different macro and small 5G BS implementation and operation scenarios and for rural, urban, dense-urban and indoor-hotspot device density classes (areas). The results of analyses reveal a strong influence of increasing DV trends on standardized data and coverage EE metrics of 5G HetNets. For every device density class characterized with increased DVs, we here elaborate on the process of achieving the best and worse combination of data and coverage EE metrics for each of the analyzed 5G BSs deployment and operation approaches. This elaboration is further extended on the analyses of the impact of 5G RAN instant power consumption and 5G RAN yearly energy consumption on values of standardized EE metrics. The presented analyses can serve as a reference in the selection of the most appropriate 5G BS deployment and operation approach, which will simultaneously ensure the transfer of permanently increasing DVs in a specific device density class and the highest possible levels of data and coverage EE metrics.
随着移动用户和万物互联设备数量的快速增长，在未来十年中，将需要更多的网络容量来容纳这种数据量（DV）的持续增长。为了满足如此庞大的 DV 增长，第五代（5G）和未来第六代（6G）移动网络的实施将基于由宏基站（BS）组成的异构网络（HetNets），这些基站专门用于确保基本信号覆盖和容量，以及小基站专门用于满足热点位置增加的 DV 容量。一种能够适应不断增长的 DV 的方法是通过在网络中部署新的 BS 来增加网络容量，随着 DV 的增加来满足容量需求。这种方法对移动网络运营商（MNO）来说是一个实施挑战，这反映在移动网络无线电接入部分的功耗增加和网络能源效率（EE）降低。在这项研究中，通过使用标准化数据和覆盖 EE 指标，分析了 2020 年代 DV 预期增长对 5G 无线电接入网络（RAN）的 EE 的影响。对 5G 宏基站和小基站的五种不同实施和运行场景以及农村、城市、密集城市和室内热点设备密度类别的 RAN 进行了分析。分析结果表明，不断增长的 DV 趋势对 5G HetNets 的标准化数据和覆盖 EE 指标有很大影响。对于每个具有增长的 DV 的设备密度类，我们在这里详细说明了实现每种分析的 5G BS 部署和运行方法的最佳和最差数据和覆盖 EE 指标组合的过程。进一步扩展了对 5G RAN 即时功率消耗和 5G RAN 年能耗对标准化 EE 指标值的影响的分析。提出的分析可以作为选择最合适的 5G BS 部署和运行方法的参考，该方法将同时确保在特定设备密度类中永久增加的 DV 的传输以及数据和覆盖 EE 指标的最高可能水平。
